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# Copyright 2024 The Flax Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for flax.traverse_util."""
import collections
import jax
import jax.numpy as jnp
import numpy as np
import optax
from absl.testing import absltest
import flax
from flax import traverse_util
from flax.core import freeze
# Parse absl flags test_srcdir and test_tmpdir.
jax.config.parse_flags_with_absl()
class Foo:
def __init__(self, foo, bar=None):
self.foo = foo
self.bar = bar
def __eq__(self, other):
return self.foo == other.foo and self.bar == other.bar
Point = collections.namedtuple('Point', ['x', 'y'])
class TraversalTest(absltest.TestCase):
def test_traversal_id(self):
x = 1
traversal = traverse_util.t_identity
self.assertEqual(list(traversal.iterate(x)), [1])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, 2)
def test_traverse_item(self):
x = {'foo': 1}
traversal = traverse_util.t_identity['foo']
self.assertEqual(list(traversal.iterate(x)), [1])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, {'foo': 2})
def test_traverse_tuple_item(self):
x = (1, 2, 3)
traversal = traverse_util.t_identity[1]
self.assertEqual(list(traversal.iterate(x)), [2])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, (1, 4, 3))
def test_traverse_tuple_items(self):
x = (1, 2, 3, 4)
traversal = traverse_util.t_identity[1:3]
self.assertEqual(list(traversal.iterate(x)), [2, 3])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, (1, 4, 6, 4))
def test_traverse_namedtuple_item(self):
x = Point(x=1, y=2)
traversal = traverse_util.t_identity[1]
self.assertEqual(list(traversal.iterate(x)), [2])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, Point(x=1, y=4))
def test_traverse_attr(self):
x = Foo(foo=1)
traversal = traverse_util.t_identity.foo
self.assertEqual(list(traversal.iterate(x)), [1])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, Foo(foo=2))
def test_traverse_namedtuple_attr(self):
x = Point(x=1, y=2)
traversal = traverse_util.t_identity.y
self.assertEqual(list(traversal.iterate(x)), [2])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, Point(x=1, y=4))
def test_traverse_dataclass_attr(self):
x = Point(x=1, y=2)
traversal = traverse_util.t_identity.y
self.assertEqual(list(traversal.iterate(x)), [2])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, Point(x=1, y=4))
def test_traverse_merge(self):
x = [{'foo': 1, 'bar': 2}, {'foo': 3, 'bar': 4}]
traversal_base = traverse_util.t_identity.each()
traversal = traversal_base.merge(
traverse_util.TraverseItem('foo'), traverse_util.TraverseItem('bar')
)
self.assertEqual(list(traversal.iterate(x)), [1, 2, 3, 4])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, [{'foo': 2, 'bar': 4}, {'foo': 6, 'bar': 8}])
def test_traverse_each(self):
x = [{'foo': 1}, {'foo': 2}]
traversal = traverse_util.t_identity.each()['foo']
self.assertEqual(list(traversal.iterate(x)), [1, 2])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, [{'foo': 2}, {'foo': 4}])
def test_traverse_each_dict(self):
x = {'foo': 1, 'bar': 2}
traversal = traverse_util.t_identity.each()
self.assertEqual(list(traversal.iterate(x)), [1, 2])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, {'foo': 2, 'bar': 4})
def test_traverse_tree(self):
x = [{'foo': 1}, {'bar': 2}]
traversal = traverse_util.t_identity.tree()
self.assertEqual(list(traversal.iterate(x)), [1, 2])
y = traversal.update(lambda x: x + x, x)
self.assertEqual(y, [{'foo': 2}, {'bar': 4}])
def test_traverse_filter(self):
x = [1, -2, 3, -4]
traversal = traverse_util.t_identity.each().filter(lambda x: x < 0)
self.assertEqual(list(traversal.iterate(x)), [-2, -4])
y = traversal.update(lambda x: -x, x)
self.assertEqual(y, [1, 2, 3, 4])
def test_traversal_set(self):
x = {'foo': [1, 2]}
traversal = traverse_util.t_identity['foo'].each()
y = traversal.set([3, 4], x)
self.assertEqual(y, {'foo': [3, 4]})
with self.assertRaises(ValueError):
traversal.set([3], x) # too few values
with self.assertRaises(ValueError):
traversal.set([3, 4, 5], x) # too many values
def test_flatten_dict(self):
xs = {'foo': 1, 'bar': {'a': 2, 'b': {}}}
flat_xs = traverse_util.flatten_dict(xs)
self.assertEqual(
flat_xs,
{
('foo',): 1,
('bar', 'a'): 2,
},
)
flat_xs = traverse_util.flatten_dict(freeze(xs))
self.assertEqual(
flat_xs,
{
('foo',): 1,
('bar', 'a'): 2,
},
)
flat_xs = traverse_util.flatten_dict(xs, sep='/')
self.assertEqual(
flat_xs,
{
'foo': 1,
'bar/a': 2,
},
)
def test_unflatten_dict(self):
expected_xs = {'foo': 1, 'bar': {'a': 2}}
xs = traverse_util.unflatten_dict(
{
('foo',): 1,
('bar', 'a'): 2,
}
)
self.assertEqual(xs, expected_xs)
xs = traverse_util.unflatten_dict(
{
'foo': 1,
'bar/a': 2,
},
sep='/',
)
self.assertEqual(xs, expected_xs)
def test_flatten_dict_keep_empty(self):
xs = {'foo': 1, 'bar': {'a': 2, 'b': {}}}
flat_xs = traverse_util.flatten_dict(xs, keep_empty_nodes=True)
self.assertEqual(
flat_xs,
{
('foo',): 1,
('bar', 'a'): 2,
('bar', 'b'): traverse_util.empty_node,
},
)
xs_restore = traverse_util.unflatten_dict(flat_xs)
self.assertEqual(xs, xs_restore)
def test_flatten_dict_is_leaf(self):
xs = {'foo': {'c': 4}, 'bar': {'a': 2, 'b': {}}}
flat_xs = traverse_util.flatten_dict(
xs, is_leaf=lambda k, x: len(k) == 1 and len(x) == 2
)
self.assertEqual(
flat_xs,
{
('foo', 'c'): 4,
('bar',): {'a': 2, 'b': {}},
},
)
xs_restore = traverse_util.unflatten_dict(flat_xs)
self.assertEqual(xs, xs_restore)
class ModelParamTraversalTest(absltest.TestCase):
def test_only_works_on_model_params(self):
traversal = traverse_util.ModelParamTraversal(lambda *_: True)
with self.assertRaises(ValueError):
list(traversal.iterate([]))
def test_param_selection(self):
params = {
'x': {
'kernel': 1,
'bias': 2,
'y': {
'kernel': 3,
'bias': 4,
},
'z': {},
},
}
expected_params = {
'x': {
'kernel': 2,
'bias': 2,
'y': {
'kernel': 6,
'bias': 4,
},
'z': {},
},
}
names = []
def filter_fn(name, _):
names.append(name) # track names passed to filter_fn for testing
return 'kernel' in name
traversal = traverse_util.ModelParamTraversal(filter_fn)
values = list(traversal.iterate(params))
configs = [
(params, expected_params),
(flax.core.FrozenDict(params), flax.core.FrozenDict(expected_params)),
]
for model, expected_model in configs:
self.assertEqual(values, [1, 3])
self.assertEqual(
set(names), {'/x/kernel', '/x/bias', '/x/y/kernel', '/x/y/bias'}
)
new_model = traversal.update(lambda x: x + x, model)
self.assertEqual(new_model, expected_model)
def test_path_value(self):
params_in = {'a': {'b': 10, 'c': 2}}
params_out = traverse_util.path_aware_map(
lambda path, x: x + 1 if 'b' in path else -x, params_in
)
self.assertEqual(params_out, {'a': {'b': 11, 'c': -2}})
def test_path_aware_map_with_multi_transform(self):
params = {
'linear_1': {'w': jnp.zeros((5, 6)), 'b': jnp.zeros(5)},
'linear_2': {'w': jnp.zeros((6, 1)), 'b': jnp.zeros(1)},
}
gradients = jax.tree_util.tree_map(jnp.ones_like, params) # dummy gradients
param_labels = traverse_util.path_aware_map(
lambda path, x: 'kernel' if 'w' in path else 'bias', params
)
tx = optax.multi_transform(
{'kernel': optax.sgd(1.0), 'bias': optax.set_to_zero()}, param_labels
)
state = tx.init(params)
updates, new_state = tx.update(gradients, state, params)
new_params = optax.apply_updates(params, updates)
self.assertTrue(
np.allclose(new_params['linear_1']['b'], params['linear_1']['b'])
)
self.assertTrue(
np.allclose(new_params['linear_2']['b'], params['linear_2']['b'])
)
self.assertFalse(
np.allclose(new_params['linear_1']['w'], params['linear_1']['w'])
)
self.assertFalse(
np.allclose(new_params['linear_2']['w'], params['linear_2']['w'])
)
def test_path_aware_map_with_masked(self):
params = {
'linear_1': {'w': jnp.zeros((5, 6)), 'b': jnp.zeros(5)},
'linear_2': {'w': jnp.zeros((6, 1)), 'b': jnp.zeros(1)},
}
gradients = jax.tree_util.tree_map(jnp.ones_like, params) # dummy gradients
params_mask = traverse_util.path_aware_map(
lambda path, x: 'w' in path, params
)
tx = optax.masked(optax.sgd(1.0), params_mask)
state = tx.init(params)
updates, new_state = tx.update(gradients, state, params)
new_params = optax.apply_updates(params, updates)
self.assertTrue(
np.allclose(new_params['linear_1']['b'], gradients['linear_1']['b'])
)
self.assertTrue(
np.allclose(new_params['linear_2']['b'], gradients['linear_2']['b'])
)
self.assertTrue(
np.allclose(new_params['linear_1']['w'], -gradients['linear_1']['w'])
)
self.assertTrue(
np.allclose(new_params['linear_2']['w'], -gradients['linear_2']['w'])
)
def test_path_aware_map_with_empty_nodes(self):
params_in = {'a': {'b': 10, 'c': 2}, 'b': {}}
params_out = traverse_util.path_aware_map(
lambda path, x: x + 1 if 'b' in path else -x, params_in
)
self.assertEqual(params_out, {'a': {'b': 11, 'c': -2}, 'b': {}})
if __name__ == '__main__':
absltest.main()